Trajectory calibration approach using a flexible particle filter for PNS

An applicable inertial-based pedestrian navigation system (PNS) is often composed of two stages: trajectory-generation stage and trajectory-calibration stage. As a mature algorithm, ZUPT (Zero-velocity Update)-aided EKF (Extended Kalman Filter) is commonly deployed to resolve trajectories of pedestrians, with short-term drifts suppressed during stance phase. In the trajectory-calibration stage, many a priori knowledge based methods are adopted to suppress or even eliminate long-term drifts. In this paper, we propose a particle filter based approach for trajectory calibration with awareness of the rectangular structures of buildings. The navigation frame is divided into eight directions, including four “domain” directions and four complementary directions. The “domain” directions are consistent with the layout of the rectangular building structure, while the complementary directions are set to avoid abrupt adjustment in minority situations, such as turnings and random walks. In the particle filter framework, the headings and positions from the previous stage are adjusted by assigning weight to particles according to a Gaussian function, which over-weight particles nearby the eight directions and de-weight those more far away from them. Along with the resampling procedure, long-term heading drifts are suppressed by gradually eliminating particles at odds with the rectangular building structure. To verify the accuracy and robustness of the proposed approach, the authors have conducted many real-world experiments in different scenarios. In a typical office building experiment with corridors and stairs, the location error is less than 1% of total walking distance, which is acceptable in most applications. Another relatively large-scale walk in a mall with curves and lines demonstrates the adaptability of our approach to some special situations with complex paths. The results have shown that our approach can perform accurate, continuous and stable positioning.